Evidence map›Paper›PMID 41787223›Full record

ReviewTherapeutic innovation & regulatory science2026

Applications and Challenges of Artificial Intelligence and Big Data in Drug Regulation.

Zhao Liu, Yang Zheng, Jun Fang, Lin Yuan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhao LiuInstitute of Executive Development, National Medical Products Administration, Beijing, 100073, China.
Yang ZhengInstitute of Executive Development, National Medical Products Administration, Beijing, 100073, China.
Jun FangInstitute of Executive Development, National Medical Products Administration, Beijing, 100073, China. 13661318348@163.com.
Lin YuanChina Society for Drug Regulation, Beijing, 100050, China. ylyl1220@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) and big data are increasingly applied in drug regulation and have demonstrated significant potential worldwide. The U.S. Food and Drug Administration (FDA) has developed a relatively comprehensive approach through strategic frameworks, regulatory guidelines, and pilot programs. The European Medicines Agency (EMA) has promoted AI adoption via the Big Data Task Force, DARWIN EU

Indexed as

Artificial IntelligenceBig DataDrug and Narcotic ControlHumansUnited StatesUnited States Food and Drug AdministrationArtificial intelligenceBig dataData governanceDrug regulationethics

Identifiers

PMID41787223

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.